Low-level Visual Motion Research Articles

No evidence that monkeys attribute mental states to animated shapes in the Heider–Simmel videos

Human Theory of Mind (ToM) is so automatic and pervasive that we spontaneously attribute mental states to animated abstract shapes, as evidenced by the classic Heider–Simmel findings. The extent to which this represents a fundamental characteristic of primate social cognition is debated. Prior research suggests that monkeys spontaneously predict behavior and attribute basic goals to conspecifics, but it remains unclear whether, like humans, they spontaneously ascribe mental states to animated shapes. Here, we address this question by analyzing rhesus monkeys’ viewing patterns of the classic Heider–Simmel animations. We hypothesized that if rhesus monkeys also spontaneously attribute mental states to animated shapes, then, like humans, they would have the longest fixation durations for theory of mind animations, medium duration fixation for goal-directed animations, and shortest fixations for animations with random motion. In contrast, if attributing mental states to animations is specific to humans and perhaps other apes, then we predict no differences in looking time across animation categories. Unlike humans, monkeys did not fixate longer on ToM videos. Critically, monkeys’ viewing patterns did not correlate with humans’ viewing patterns or intentionality ratings from previously published research. The only major difference in viewing patterns between animation categories tracked differences in low-level visual motion. Thus, monkeys do not view the classic Heider–Simmel animations like humans do and we found no evidence that they spontaneously attribute mental states to animated shapes.

Hearing what you see: Distinct excitatory and disinhibitory mechanisms contribute to visually-evoked auditory sensations

Visual motion or flashing lights can evoke auditory sensations in some people. This large-scale internet study aimed to validate a combined subjective/objective test of the genuineness of this putative form of synaesthesia (visually-evoked auditory response, vEAR). Correlations were measured between each individual's ratings of the vividness of auditory sensations evoked by a series of looping videos, and measurement of the videos' physical low-level motion energy, calculated using Adelson and Bergen’s (1985) computational model of low-level visual motion processing. The strength of this association for each individual provided a test of how strongly subjective vEAR was driven by objective motion energy (‘ME-sensitivity’). A second aim was to infer whether vEAR depends on cortical excitation and/or disinhibition of early visual and/or auditory brain areas. To achieve this, correlations were measured between the above vEAR measures and visual contrast surround-suppression, which is thought to index lateral inhibition in the early visual system. As predicted by a disinhibition account of vEAR, video ratings were overall higher in individuals showing weaker surround-suppression. Interestingly, surround-suppression and ME-sensitivity did not correlate. Additionally, both surround-suppression and ME-sensitivity each independently predicted different clusters of trait measures selected for their possible association with cortical excitability and/or disinhibition: Surround-suppression was associated with vEAR self-ratings and auditory-evoked visual phosphenes, while ME-sensitivity was independently associated with ratings of other traits including susceptibility to migraine and pattern glare. Altogether, these results suggest there are two independent mechanisms underlying vEAR and its associated traits, based putatively on cortical disinhibition versus excitability.

A common neural substrate for processing scenes and egomotion-compatible visual motion

Neuroimaging studies have revealed two separate classes of category-selective regions specialized in optic flow (egomotion-compatible) processing and in scene/place perception. Despite the importance of both optic flow and scene/place recognition to estimate changes in position and orientation within the environment during self-motion, the possible functional link between egomotion- and scene-selective regions has not yet been established. Here we reanalyzed functional magnetic resonance images from a large sample of participants performing two well-known “localizer” fMRI experiments, consisting in passive viewing of navigationally relevant stimuli such as buildings and places (scene/place stimulus) and coherently moving fields of dots simulating the visual stimulation during self-motion (flow fields). After interrogating the egomotion-selective areas with respect to the scene/place stimulus and the scene-selective areas with respect to flow fields, we found that the egomotion-selective areas V6+ and pIPS/V3A responded bilaterally more to scenes/places compared to faces, and all the scene-selective areas (parahippocampal place area or PPA, retrosplenial complex or RSC, and occipital place area or OPA) responded more to egomotion-compatible optic flow compared to random motion. The conjunction analysis between scene/place and flow field stimuli revealed that the most important focus of common activation was found in the dorsolateral parieto-occipital cortex, spanning the scene-selective OPA and the egomotion-selective pIPS/V3A. Individual inspection of the relative locations of these two regions revealed a partial overlap and a similar response profile to an independent low-level visual motion stimulus, suggesting that OPA and pIPS/V3A may be part of a unique motion-selective complex specialized in encoding both egomotion- and scene-relevant information, likely for the control of navigation in a structured environment.

Vection induced by low-level motion extracted from complex animation films.

This study examined the contributions of low-, mid- and high-level visual motion information to vection. We compared the vection experiences induced by hand-drawn and computer-generated animation clips to those induced by versions of these movies that contained only their pure optic flow. While the original movies were found to induce longer and stronger vection experiences than the pure optic flow, vection onsets were not significantly altered by removing the mid- and high-level information. We conclude that low-level visual motion information appears to be important for vection induction, whereas mid- and higher-level display information appears to be important for sustaining and strengthening this vection after its initial induction.

Detecting Biological Motion for Human–Robot Interaction: A Link between Perception and Action

One of the fundamental skill supporting safe and comfortable interaction between humans is their capability to understand intuitively each other's actions and intentions. At the basis of this ability is a special-purpose visual processing that human brain has developed to comprehend human motion. Among the first building blocks enabling the bootstrapping of such visual processing is the ability to detect movements performed by biological agents in the scene, a skill mastered by human babies in the first days of their life. In this paper we present a computational model based on the assumption that such visual ability must be based on local low-level visual motion features which are independent of shape, such as the configuration of the body, and perspective. Moreover, we implement it on the humanoid robot iCub, embedding it into a software architecture that leverages the regularities of biological motion also to control robot attention and oculo-motor behaviors. In essence, we put forth a model in which the regularities of biological motion link perception and action enabling a robotic agent to follow a human-inspired sensory-motor behavior. We posit that this choice facilitates mutual understanding and goal prediction during collaboration, increasing the pleasantness and safety of the interaction.

Audiovisual associations alter the perception of low-level visual motion.

Motion perception is a pervasive nature of vision and is affected by both immediate pattern of sensory inputs and prior experiences acquired through associations. Recently, several studies reported that an association can be established quickly between directions of visual motion and static sounds of distinct frequencies. After the association is formed, sounds are able to change the perceived direction of visual motion. To determine whether such rapidly acquired audiovisual associations and their subsequent influences on visual motion perception are dependent on the involvement of higher-order attentive tracking mechanisms, we designed psychophysical experiments using regular and reverse-phi random dot motions isolating low-level pre-attentive motion processing. Our results show that an association between the directions of low-level visual motion and static sounds can be formed and this audiovisual association alters the subsequent perception of low-level visual motion. These findings support the view that audiovisual associations are not restricted to high-level attention based motion system and early-level visual motion processing has some potential role.

Modelling fast forms of visual neural plasticity using a modified second-order motion energy model.

The Adelson-Bergen motion energy sensor is well established as the leading model of low-level visual motion sensing in human vision. However, the standard model cannot predict adaptation effects in motion perception. A previous paper Pavan et al.(Journal of Vision 10:1-17, 2013) presented an extension to the model which uses a first-order RC gain-control circuit (leaky integrator) to implement adaptation effects which can span many seconds, and showed that the extended model's output is consistent with psychophysical data on the classic motion after-effect. Recent psychophysical research has reported adaptation over much shorter time periods, spanning just a few hundred milliseconds. The present paper further extends the sensor model to implement rapid adaptation, by adding a second-order RC circuit which causes the sensor to require a finite amount of time to react to a sudden change in stimulation. The output of the new sensor accounts accurately for psychophysical data on rapid forms of facilitation (rapid visual motion priming, rVMP) and suppression (rapid motion after-effect, rMAE). Changes in natural scene content occur over multiple time scales, and multi-stage leaky integrators of the kind proposed here offer a computational scheme for modelling adaptation over multiple time scales.

Static sound timing alters sensitivity to low-level visual motion

Visual motion processing is essential to survival in a dynamic world and is probably the best-studied facet of visual perception. It has been recently discovered that the timing of brief static sounds can bias visual motion perception, an effect attributed to "temporal ventriloquism" whereby the timing of the sounds "captures" the timing of the visual events. To determine whether this cross-modal interaction is dependent on the involvement of higher-order attentive tracking mechanisms, we used near-threshold motion stimuli that isolated low-level pre-attentive visual motion processing. We found that the timing of brief sounds altered sensitivity to these visual motion stimuli in a manner that paralleled changes in the timing of the visual stimuli. Our findings indicate that auditory timing impacts visual motion processing very early in the processing hierarchy and without the involvement of higher-order attentional and/or position tracking mechanisms.

Individual differences in low-level visual motion processing

Individual differences in low-level visual motion processing

Two Distinct Visual Motion Mechanisms for Smooth Pursuit: Evidence from Individual Differences

Smooth-pursuit eye velocity to a moving target is more accurate after an initial catch-up saccade than before, an enhancement that is poorly understood. We present an individual-differences-based method for identifying mechanisms underlying a physiological response and use it to test whether visual motion signals driving pursuit differ pre- and postsaccade. Correlating moment-to-moment measurements of pursuit over time with two psychophysical measures of speed estimation during fixation, we find two independent associations across individuals. Presaccadic pursuit acceleration is predicted by the precision of low-level (motion-energy-based) speed estimation, and postsaccadic pursuit precision is predicted by the precision of high-level (position-tracking) speed estimation. These results provide evidence that a low-level motion signal influences presaccadic acceleration and an independent high-level motion signal influences postsaccadic precision, thus presenting a plausible mechanism for postsaccadic enhancement of pursuit.